Mining Frequent Itemsets Using Genetic Algorithm
, 2010 In general frequent itemsets are generated from large data sets by applying association rule mining algorithms like Apriori, Partition, Pincer-Search, Incremental, Border algorithm etc., which take too much computer time to compute all the frequent ...
Biswas, Sushanta +3 more
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Incremental Closed Frequent Itemsets Mining-Based Approach Using Maximal Candidates
IEEE AccessIncremental frequent itemset mining aims to efficiently update frequent itemsets without recalculating them from scratch, making it suitable for streaming data and real-time analytics.
Mohammed A. Al-Zeiadi +1 more
doaj +1 more source
Proposed Algorithm for Extracting Association Rule Depend on Closed Frequent Itemset (EACFI) [PDF]
Engineering and Technology Journal, 2011 Association rules are important one of data mining activities. All algorithms of association rule mining consist of finding frequency of itemsets, which satisfy a minimum support threshold, and then compute confidence percentage for each k-itemsets to ...
Emad k. Jbbar, Yaser Munther
doaj +1 more source
Quantum algorithm for association rules mining
, 2016 Association rules mining (ARM) is one of the most important problems in knowledge discovery and data mining. Given a transaction database that has a large number of transactions and items, the task of ARM is to acquire consumption habits of customers by ...
Gao, Fei +3 more
core +2 more sources
An Efficient Rigorous Approach for Identifying Statistically Significant Frequent Itemsets [PDF]
, 2009 As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is becoming a major challenge in data mining applications.
Kirsch, Adam +5 more
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Incremental Updating Algorithm of Parallel Association Rule Based on MapReduce [PDF]
Jisuanji gongcheng, 2016 Under the environment of big data,the traditional association rule mining algorithms have lower efficiency caused by the rapidly increasing data.Aiming at the problem,this paper proposes a parallel incremental updating algorithm of association rules ...
CHENG Guang,WANG Xiaofeng
doaj +1 more source
Knowledge, false beliefs and fact-driven perceptions of Muslims in Australia: a national survey
, 2005 Mining frequent itemsets is one of the main problems in data mining. Much effort went into developing efficient and scalable algorithms for this problem.
Bart Goethals, Toon Calders
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FP-tree and COFI Based Approach for Mining of Multiple Level Association Rules in Large Databases
, 2010 In recent years, discovery of association rules among itemsets in a large database has been described as an important database-mining problem. The problem of discovering association rules has received considerable research attention and several ...
Kumar, Parveen +2 more
core +1 more source
Generic Itemset Mining Based on Reinforcement Learning
IEEE Access, 2022 One of the biggest problems in itemset mining is the requirement of developing a data structure or algorithm, every time a user wants to extract a different type of itemsets.
Kazuma Fujioka, Kimiaki Shirahama
doaj +1 more source
Mining frequent closed itemsets out of core [PDF]
Proceedings of the 2006 SIAM International Conference on Data Mining, 2006 Extracting frequent itemsets is an important task in many data mining applications. When data are very large, it becomes mandatory to perform the mining task by using an external memory algorithm, but only a few of these algorithms have been proposed so far.
LUCCHESE, Claudio +2 more
openaire +3 more sources